The ‘Ecology of Games Framework’ (EG) combines insights from many approaches to analyze ‘institutional complexity’ and ‘complex institutional systems’.
The focus is on actors learning how to secure ‘mutually beneficial outcomes’, cooperating to produce and deliver agreed solutions, and bargaining within a system over which no actor has control. Therefore, it is worth reading the posts on game theory, the IAD, and SES first (especially if, like me, you associated ‘game’ with tig, then Monopoly, then The Wire).
In simple games, we need only analyse the interaction between a small number of actors with reference to one set of self-contained rules providing clear sanctions or payoffs. In real world policymaking, many different games take place at the same time in different venues.
Some policy games may be contained within a geographical area – such as California – but there are no self-contained collective action problems:
Examples such as ‘biodiversity’, ‘ecology’ or ‘environmental’ policies command a collection of interdependent policies relating to issues like local planning, protected species, water management, air pollution, transport, energy use, and contributors to such policies or policy problems in other areas of government (such as public services).
Each contributor to policy may come from different institutions associated with many policymaking venues spread across many levels and types of government.
Consequently, many games interact with each other. The same actor might participate in multiple games subject to different rules. Further, each game produces ‘externalities’ for the others; the ‘payoffs’ to each game are connected and complicated.
A focus on ‘complex adaptive systems’ suggests that central governments do not have the resources to control – or understand fully – interaction at this frequency and scale. Rather, policymaking influences are:
Internal to the game, when actors (a) follow and shape the rules of each institution, and (b) learn through trial and error.
External to the game, when physical resources change, or central levels of government change the resources of local actors.
Insights from the wider literature
The EG brings in wider insights – from theories in the 500 and 1000 Words series – to analyse this process. Examples include:
As with the IAD, the EG emphasis is on (a) finding solutions to complex (largely environmental) policy problems, with reference to (b) initiatives consistent with self-organising systems such as ‘collaborative governance’. Like most posts in this series, it rejects a naïve attachment to a single powerful central government. Policymaking is multi-centric, and solutions to complex problems will emerge in that context.
Rational choice theory provides a way of thinking about collective action problems. There is great potential for choices made by individuals to have an adverse societal effect when there is an absence of trust, obligation, or other incentives to cooperate. People may have collective aims that require cooperation, but individual incentives to defect. While the action of one individual makes little difference, the sum total of individual actions may be catastrophic.
Simple ‘games’ provide a way to think about these issues logically, by limiting analysis to very specific situations under rather unrealistic conditions, before we consider possible solutions under more realistic conditions. For example, in simple games we assume that individuals pursue the best means to fulfil their preferences: they are able to act ‘optimally’ by processing all relevant information to rank-order their preferences consistently.
Go with it just now, and then we can consider what to do next.
The ‘prisoner’s dilemma’
Two people are caught red-handed and arrested for a minor crime, placed in separate rooms and invited to confess to a major crime (they both did it and the police know it but can’t prove it). The payoffs are:
If Paul confesses and Linda doesn’t, then Paul walks free and Linda receives a 10 year jail sentence (or vice versa)
If both confess they receive a much higher sentence (8 years) than if neither confesses (1 year).
Also assume that they take no benefit from the shorter sentence of the other person (a non-cooperative game).
It demonstrates a collective action problem: although the best outcome for the group requires that neither confess (both would go to jail for a total of 2 years), the actual outcome is that both confess (16 years). The latter represents the ‘Nash equilibrium’ since neither would be better off by changing their strategy unilaterally. Think of it from an individual’s perspective:
Imagine Paul will confess. Linda knows that if she stays silent, she gets suckered into 10 years. If she confesses, she gets 8.
Imagine Paul will stay silent. Linda knows that if she stays silent, she gets 1 year. If she confesses, she suckers Paul into 10.
The effect of Paul and Linda acting as individuals is that they are worse off collectively. Both ‘defect’ (confess) when they should ‘cooperate’ (stay silent).
The ‘logic of collective action’
Olson argues that, as the membership of an interest group rises, so does:
(a) the belief among individuals that their contribution to the group would make little difference and
(b) their ability to ‘free ride’.
I may applaud the actions of a group, but can – and will try to – enjoy the outcomes without leaving my sofa, paying them, or worrying that they will fail without me or punish me for not getting involved.
The ‘tragedy of the commons’
The scenario is that a group of farmers share a piece of land that can only support so many cattle before deteriorating and becoming useless. Although each farmer recognizes the collective benefit to an overall maximum number of cattle, each calculates that the marginal benefit she takes from one extra cow for herself exceeds the extra cost of over grazing to the group. Individuals place more value on the resources they extract for themselves now than the additional rewards they could all extract in the future.
The tragedy is that if all farmers act on the same calculation then they will destroy the common resource. The group is too large to track individual behaviour, individuals place more value on current over future consumption, and there is low mutual trust, with minimal motive and opportunity to produce and enforce binding agreements
This ‘tragedy’ sums up current anxieties about one of the defining problems of our time: global ‘common pool resources’ are scarce and the world’s population and consumption levels are rising; there is no magic solution; and, collective action is necessary but not guaranteed. We may value sustainable water, air, energy, forests, crops, and fishing stocks, but find it difficult to imagine how our small contribution to consumption will make much difference. As a group we fear climate change and seek to change our ways but, as individuals, contribute to the problem.
Overall, these scenarios suggest that individuals have weak incentives to cooperate even if it is in their interests and they agree to do so. This problem famously prompted Hardin (to recommend ‘mutual coercion, mutually agreed upon’ to ensure collective action.
What happens when there are many connected games?
In real life, it is almost impossible to find such self-contained and one-off games.In many repeated – or connected – games, the players know that thereare wider or longer-term consequences to defection.
In ‘nested games’, the behaviour of individuals often seems weird in one game until we recognise their involvement in a series. It may pay off to act ‘irrationally’ in the short term to support a longer-term strategy, or to lose in one to win in another.
In an ‘ecology of games’, many overlapping games take place at roughly the same time, and players to learn how to play one game while keeping an eye on many others, while some key players encourage a wider set of rules under which all games operate.
Evolutionary game theory explores how behaviour changes over multiple games to reflect factors such as (a) feedback and learning from trial and error, and (b) norms and norm enforcement.
For example, player 2 may pursue a ‘tit-for-tat’ strategy. She cooperates at first, then mimics the other player’s previous choice: defecting, to punish the other player’s defection, or cooperating if the other player cooperated. Knowledge of this strategy could provide player 1 with the incentive to cooperate. Further, norms develop when players enforce and expect sanctions for non-cooperation, foster socialisation to discourage norm violation, and some norms become laws.
In other words, this focus on the rules of repeated games gives us more hope than the tragedy of the commons. Indeed, it underpin Ostrom’s famous analysis of the conditions under which people can govern the commons more effectively.
These posts introduce you to key concepts in the study of public policy. They are all designed to turn a complex policymaking world into something simple enough to understand. Some of them focus on small parts of the system. Others present ambitious ways to explain the system as a whole. The wide range of concepts should give you a sense of a variety of studies out there, but my aim is to show you that these studies have common themes.